Evidence map›Paper›PMID 41693555›Full record

ArticleCirculation. Population health and outcomes2026

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China.

Xiaoting Peng, Chao Wu, Huixian Li, Lianting Hu, Yilin Niu, Yunyi Li, Shuai Huang, Xueli Zhang, Entao Liu, Huan Ma and 3 more

Abstract read
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Article in Circulation. Population health and outcomes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Xiaoting Peng *School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China (X.P., H. Li, H. Liang).ORCID 0009-0000-0187-9991
Chao Wu *Stanley and Judith Frankel Institute for Heart and Brain Health, University of Michigan Medical Center, Ann Arbor (C.W.).ORCID 0000-0003-0863-9207
Huixian LiSchool of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China (X.P., H. Li, H. Liang).ORCID 0000-0001-5722-8602
Lianting HuWuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Hunan Province, China (L.H.).ORCID 0000-0003-4573-3809
Yilin NiuMedical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China (X.P., H. Li, Y.N., S.H., H. Liang, D.L.).ORCID 0000-0001-8507-8533
Yunyi LiSchool of Software Engineering, South China University of Technology, Guangzhou, Guangdong Province, China (Y.L.).
Shuai HuangMedical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China (X.P., H. Li, Y.N., S.H., H. Liang, D.L.).ORCID 0000-0002-0387-8404
Xueli ZhangInstitute of Scientific Instrumentation, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, PR China (X.Z.).
Entao LiuDepartment of Nuclear Medicine, Guangdong Provincial People's Hospital, Guangzhou, China (E.L.).ORCID 0000-0002-0388-5540
Huan Ma *Guangdong Provincial Cardiovascular Institute, Guangzhou, China (S.H., H.M., D.L.).ORCID 0000-0003-4150-9201
Qingshan Geng *Department of Cardiology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Guangdong Province, China (Q.G.).
Huiying Liang *School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China (X.P., H. Li, H. Liang).
Dantong Li *Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China (X.P., H. Li, Y.N., S.H., H. Liang, D.L.).ORCID 0000-0002-8418-0496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, while the reference standard, positron emission tomography/computed tomography, is costly and less accessible. We aimed to characterize mental stress-induced myocardial ischemia using multistage ECG analysis and machine learning to improve early, noninvasive detection.

methodsWe enrolled 2 female cohorts (18-75 years) from a single-center tertiary hospital in Guangzhou, China: a study cohort (2020-2021) and an independent test cohort (2022-2023). Participants included women with angina, nonobstructive coronary artery disease, and age-matched healthy controls. Multistage ECGs were recorded during 3 mental stress tasks and segmented into Rest, Stress, and Recovery phases. A total of 88 interpretable ECG variables, including morphological indices and heart rate variability, were extracted from each stage, and interstage differences were then calculated. Mental stress-induced myocardial ischemia labeling was obtained from positron emission tomography/computed tomography. Machine learning classifiers (K-nearest neighbors, logistic regression, random forest, support vector machine, extreme gradient boosting) were trained on the study cohort and evaluated in the test cohort using single-stage, multistage, and interstage features.

resultsThe study cohort (n=119, mean age 53±8 years) showed significant heart rate variability, heart rate asymmetry, and prognostic-related changes, with 103 of 264 intrastage features differing across Rest, Stress, and Recovery (

conclusionsMultistage ECG analysis, particularly heart rate variability, captures electrophysiological signatures of mental stress-induced myocardial ischemia and enhances noninvasive detection. These findings support a paradigm shift from single-phase, ischemia-focused ECG interpretation to dynamic, multivariable assessment, providing a foundation for early identification and personalized risk stratification in women with nonobstructive coronary disease.

Indexed as

ElectrocardiographyMyocardial IschemiaStress, PsychologicalAdolescentAdultAgedChinaFemaleHeart RateHumansMachine LearningMiddle AgedPositron Emission Tomography Computed TomographyProspective StudiesYoung Adultdiagnosiselectrocardiographymyocardial ischemia

Identifiers

PMID41693555
PMCPMC12986047

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.